Predictability and Model Verification of the Water and Energy Cycles: Linking Local, Regional and Global Scales Principal Investigator: Duane Waliser Updated: 8/24/09 Lessons learned What worked: TRMM-based estimates are beginning to be useful to describe heating althogh models don’t routinely output. Multi-sensor estimates of major water components beginning to describe hydrological cycle in large-scale phenomena such as MJO. What did not work: Lack of comprehensive water and energy cycle components provided from conventional model hindcast/forecast and IPCC AR4 data sets. Significant challenges remain on closing water cycle budget from satellte observations for the large time and space scales e.g., MJO. Science issue: Quantify our simulation and prediction capabilities of the water cycle and estimate its predictability, considering regional to global scales. Approach: Examine climate simulations and hindcast/forecast data sets from global models and use satellite data for verification quantities. Satellite-based data: GPCP, CMAP, AIRS, ISCCP, GLDAS, OAFlux, TRMM, SSMI, MLS, CloudSat, GRACE. Models: NCEP CFS, NASA GEOS-5, CMIP-3/IPCC Analyses: NCEP 1&2, ECMWF Study Period: 1979 and later for simulations and weather/short-term climate forecasts, 20th and 21st century for CMIP3/IPCC NOTE: The late arrival of GEOS5 products drive effort into other synergistic studies on the water cycle and climate variability (e.g, MJO). NEWS linkages: Contribute to NASA-MAP Subseasonal Project: PI S. Schubert Collaborate w/ Olson, Tao & L’Ecuyer on MJO TRMM Heating Retrievals Collaborate w/ Liu on MJO and Moisture Convergence Retrievals Collaborate w/ Pan & v.d.Dool on NCEP CFS Water Cycle Predictability & Skill Connect to CLIVAR MJO Working Group and WCRP/WWRP YOTC Program. Contribute Water Cycle Climate Changes to California Energy Commission Project Publications: Longitude-pressure distribution of seasonal mean total heating (units: K day -1 ) based on (a) EC-IFS 24h forecast; (b) ERA-40 reanalysis; (c) TRMM/TRAIN algorithm; (d) TRMM/CSH algorithm. The seasonal mean is calculated from October 1998 to March All variables are averaged over equatorial zone between 10 o S-10 o N. Jiang et al Time-pressure distributions of total heating contributed by convective (a, d), stratiform (b, e), and radiative (c, f) components based on EC-IFS forecast (left) and TRMM/TRAIN estimates (right). All variables are averaged over the equatorial eastern Indian Ocean (75-95 o E; 10 o S- 10 o N; units: K day -1 ). Jiang et al MODELING, PREDICTION AND PREDICTABILITY Waliser, D. E., K. Seo, S. Schubert, E. Njoku, 2007: Global Water Cycle Agreement in IPCC AR4 Model Simulations, Geoph. Res. Let., 34, L16705, doi: /2007GL Waliser, D., J. Kim, Y. Xue, Chao, Y., A. Eldering, R. Fovell, A. Hall, Q. Li, K. Liou, J. McWilliams, S. Kapnick, R. Vasic, Fs. De Sale, and Y. Yu, 2009, Simulating the Sierra Nevada snowpack: The impact of snow albedo and multi-layer snow physics, Bienniel California Climate Change Center Report, CEC XXX. To be submitted to a special issue of Climatic Change. Kim, J., Y. Chao, A. Eldering, R. Fovell, A. Hall, Q. Li, K. Liou, J. McWilliams, D. Waliser, Y. Xue, and Sarah Kapnick, 2009: A projection of the cold season hydroclimate in California in mid-21st century under the SRES-A1B emission scenario, Bienniel California Climate Change Center Report, CEC XXX. To be submitted to a special issue of Climatic Change. Jiang, X., D.E. Waliser, H.L. Pan, H. van den Dool, S. Schubert, 2008: Internannual prediction skill and predictability of the global water cycle in the NCEP Coupled Forecast System. J. Climate, In Preparation. Gottschalck, J., M. Wheeler, K. Weickmann, F. Vitart, N. Savage, H. Lin, H. Hendon, D. Waliser, K. Sperber, M. Nakagawa, C. Prestrelo, M. Flatau, W. Higgins, 2009, Establishing and Assessing Operational Model MJO Forecasts: A Project of the CLIVAR Madden-Julian Oscillation Working Group, Bull. Am. Meteor. Soc., Submitted. Goswami, B.N., M. Wheeler, J. Gottschalck, and D. E. Waliser, 2008, Intraseasonal Variability and Forecasting: A Review of Recent Research, WMO Fourth International Workshop on Monsoons, October 2008, Beijing, China. To appear as a WMO Tech. Report. Sperber, K.R., and D. E. Waliser, 2008: New Approaches to Understanding, Simulating, and Forecasting the Madden-Julian Oscillation, Bulletin of the American Meteorology Society, DOI: /2008BAMS OOBSERVATIONS AND MODEL VERIFICATION Schwartz, M. J., D. E. Waliser, B. Tian, J. F. Li, D. L. Wu, J. H. Jiang, and W. G. Read, 2008: MJO in EOS MLS cloud ice and water vapor. Geophys. Res. Lett., 35, L08812, doi: /2008GL Waliser, D. E., B. J. Tian, M. J. Schwartz, X. Xie, W. T. Liu, and E. J. Fetzer, 2008: How well can satellite data characterize 1 the Water Cycle of the Madden-Julian Oscillation?. Geophys. Res. Lett., In Press. Seo, K.-W., D. E. Waliser, B. J. Tian, J. Famiglietti, and T. Syed, 2009: Evaluation of global land-to-ocean fresh water discharge and evapotranspiration using space-based observations. J. Hydrology, 373 (2009) 508–515. Fetzer, E. J., W. G. Read, D. Waliser, B. H. Kahn, B. Tian, H. Vomel, F. W. Irion, H. Su, A. Eldering, M. d. l. T. Juarez, J. H. Jiang, and V. Dang, 2008: Comparison of Upper Tropospheric Water Vapor Observations from the Microwave Limb Sounder and Atmospheric Infrared Sounder. J. Geophys. Res., 113, D22110, doi: /2008JD Jiang, X., D.E. Waliser, J.-L. Li, B. Tian, Y. L. Yung, W. Olson, M. Grecu, W.-K. Tao, S. E. Lang, 2008, Characterizing the vertical heating structure of the MJO using TRMM, J. Climate TRMM Special Issue, In Press. Waliser, D. E., and M. Moncrieff, 2008, The Year of Tropical Convection (YOTC) Science Plan: A joint WCRP - WWRP/THORPEX International Initiative. WMO/TD No. 1452, WCRP - 130, WWRP/THORPEX - No 9. WMO, Geneva, Switzerland. Couhert, A., T. Schneider, J.-L. Li, D. E. Waliser, A.M. Tompkins, 2009: The maintenance of the relative humidity of the subtropical free troposphere, J. Climate, In Press.